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Information Compression, Intelligence, Computing, and Mathematics

31 October 2013
J. Wolff
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Abstract

The "SP theory of intelligence" is based on the idea that much of human intelligence, and much of computing and mathematics, may be understood as compression of information. This article presents evidence for that idea including: advantages of information compression (IC) in terms of biology and engineering; IC in our use of shorthands and ordinary words in language; in the way we merge successive views of any one thing; in recognition; in binocular vision; in adaptation in the eye of the horseshoe crab and at the level of our conscious awareness; in children's learn of the word structure of language; in the learning of grammatical structure, and in resolving the problems of generalisation and "dirty data". Much of computing and mathematics may also be seen as IC. An equation can be a powerful means of representing information in a compressed form. The matching and unification of patterns may be seen in both computing and mathematics: in the matching and unification of names; in the reduction or removal of redundancy from unary numbers; in the workings of Post's Canonical System and the transition function in the universal Turing machine, in the way computers retrieve information from memory; in systems like Prolog; and in the query-by-example technique for information retrieval. The chunking-with-codes technique for IC may be seen in the use of named functions to avoid repetition of computer code. The schema-plus-correction technique may be seen in functions with parameters and the use of classes in object-oriented programming. And the run-length coding technique may be seen in multiplication, in division, and in several other devices in mathematics and computing. The SP theory resolves the apparent paradox of "decompression by compression", and its versatility provides further evidence for the significance of IC in human intelligence, in computing and in mathematics.

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